The invention of the present application relates generally to power generation and, more particularly, to methods and systems related to the economic and performance optimization and/or enhancement of power plants having thermal generating units.
In electric power systems, a number of participants or power plants generate electricity that is then distributed over common transmission lines to residential and commercial customers. As will be appreciated, thermal generating units, such as gas turbines, steam turbines, and combined-cycle plants, are still relied on to generate a significant portion of the power such systems require. Each of the power plants within such systems include one or more power generating units, and each of these units typically includes a control system that controls operation, and, in case of power plants having more than one generating unit, the performance of the power plant as a whole. As an example, one of the responsibilities of a plant operator is the generation of an offer curve representing the cost of power production. An offer curve typically includes an incremental variable cost curve, an average variable cost curve, or another suitable indication of variable power generating expense, which typically is expressed in dollars per megawatt-hour versus output in megawatts. It will be appreciated that an average variable cost curve may represent a cumulative cost divided by a cumulative power output for a given point, and an incremental variable cost curve may represent a change in cost divided by a change in power output. An incremental variable cost curve may be obtained, for example, by taking a first derivative of an input-output curve of the power plant that represents cost per hour versus power generated. In a combined-cycle power plant in which waste heat from a fuel burning generator is used to produce steam to power a supplemental steam turbine, an incremental variable cost curve may also be obtained with known techniques, but its derivation may be more complex.
In most power systems, a competitive process commonly referred to as economic dispatch is used to divide system load among power plants over a future time period. As part of this process, power plants periodically generate offer curves and send the offer curves to a power system authority or dispatcher. Such offer curves represent bids from the power plants to generate a portion of the electricity required by the power system over a future market period. The dispatch authority receives the offer curves from the power plants within its system and evaluates them to determine the level at which to engage each power plant so to most efficiently satisfy the predicted load requirements of the system. In doing this, the dispatch authority analyzes the offer curves and, with the objective of finding the lowest generating cost for the system, produces a commitment schedule that describes the extent to which each of the power plants will be engaged over the relevant time period.
Once the commitment schedule is communicated to the power plants, each power plant may determine the most efficient and cost-effective manner by which to satisfy its load commitment. It will be appreciated that the generating units of the power plant include control systems that monitor and control operation. When the generating units include thermal generators, such control systems govern the combustion systems and other aspects of the operation. (For illustrative purposes, both a gas turbine and combined-cycle power plants are described herein; however, it will be appreciated that certain embodiments of the present invention may be applied to other types of power generating units or be used in conjunction there with.) The control system may execute scheduling algorithms that adjust the fuel flow, inlet guide vanes, and other control inputs to ensure efficient operation of the engine. However, the actual output and efficiency of a power plant is impacted by external factors, such as variable ambient conditions, that cannot be fully anticipated. As will be appreciated, the complexity of such systems and the variability of operating conditions make it difficult to predict and control performance, which often result in inefficient operation.
Machine degradation that occurs over time is another difficult to quantify fact, which may have a significant effect on the performance of the generating units. It will be appreciated that rate of degradation, replacement of worn components, timing of maintenance routines, and other factors impact the short term performance of the plant, and thus need to be accounted for when generating cost curves during the dispatching process as well as when assessing the long term cost-effectiveness of the plant. As an example, gas turbine life typically includes limits expressed in both hours of operation and number of starts. If a gas turbine or a component thereof reaches its starts limit before its hours limit, it must be repaired or replaced, even if it has hours-based life remaining. Hours-based life in a gas turbine may be prolonged by reducing firing temperature, but this reduces efficiency of the gas turbine, which increases cost of operation. Conversely, increasing the firing temperature increases efficiency, but shortens gas turbine life and increases maintenance and/or replacement costs. As will be appreciated, life cycle cost of a thermal engine is dependent on many complex factors, while also representing a significant consideration in the economic efficiency of the power plant.
Given the complexity of modern power plants, particularly those having multiple generating units, and the market within which it competes, power plant operators continued to struggle to maximize economic return. For example, grid compliance and dispatch planning for a power plant is adversely impacted by controlling thermal generating units in an overly-static manner, i.e., using static control profiles, such as heat rate curves gathered derived from only periodic performance tests. Between these periodic updates, turbine engine performance may change (e.g., from degradation), which may affect start-up and load performance. Moreover, intraday changes in the external factors, without accounting for the same in the turbine control profiles, may lead to inefficient operation. To compensate for this type of variability, power plant operators often become overly conservative in planning for future operation, which results in underutilized generating units. Other times, plant operators are forced to operate units inefficiently to satisfy over-commitments.
Without identifying the short-term inefficiencies and/or long-term deterioration as each is realized, the conventional control systems of power plants either have to be retuned frequently, which is an expensive process, or conservatively operated so to preemptively accommodate component deterioration. The alternative is to risk violating operational boundaries that leads to excessive fatigue or failure. Similarly, conventional power plant control systems lack the ability to most cost-effectively accommodate changing conditions. As will be appreciated, this results in power plant utilization that is often far from optimal. As such, there exists a need for improved methods and systems for monitoring, modeling, and controlling power plant operation, particularly those that enable a more complete understanding of the myriad operating modes available to operators of complex modern power plants and the economic trade-offs associated with each.